Showing 12 open source projects for "artificial intelligence python"

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  • 1
    sherpa-onnx

    sherpa-onnx

    Speech-to-text, text-to-speech, and speaker recognition

    Speech-to-text, text-to-speech, and speaker recognition using next-gen Kaldi with onnxruntime without an Internet connection. Support embedded systems, Android, iOS, Raspberry Pi, RISC-V, x86_64 servers, websocket server/client, C/C++, Python, Kotlin, C#, Go, NodeJS, Java, Swift, Dart, JavaScript, Flutter.
    Downloads: 167 This Week
    Last Update:
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  • 2
    whisper.cpp

    whisper.cpp

    Port of OpenAI's Whisper model in C/C++

    whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples....
    Downloads: 371 This Week
    Last Update:
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  • 3
    PhantomBot

    PhantomBot

    PhantomBot is an actively developed open source interactive Twitch bot

    PhantomBot is an actively developed open source interactive Twitch bot with a vibrant community that provides entertainment and moderation for your channel, allowing you to focus on what matters the most to you, your game and your viewers. PhantomBot is a Twitch chat bot powered by Java. PhantomBot has many modern features out of the box such as a built-in webpanel, enhanced moderation, games, a point system, raffles, custom commands, a music player, and more. PhantomBot can also be...
    Downloads: 3 This Week
    Last Update:
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  • 4
    Porcupine

    Porcupine

    On-device wake word detection powered by deep learning

    Build always-listening yet private voice applications. Porcupine is a highly-accurate and lightweight wake word engine. It enables building always-listening voice-enabled applications. It is using deep neural networks trained in real-world environments. Compact and computationally-efficient. It is perfect for IoT. Cross-platform. Arm Cortex-M, STM32, PSoC, Arduino, and i.MX RT. Raspberry Pi, NVIDIA Jetson Nano, and BeagleBone. Android and iOS. Chrome, Safari, Firefox, and Edge. Linux...
    Downloads: 5 This Week
    Last Update:
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  • 5
    OnnxStream

    OnnxStream

    Lightweight inference library for ONNX files, written in C++

    The challenge is to run Stable Diffusion 1.5, which includes a large transformer model with almost 1 billion parameters, on a Raspberry Pi Zero 2, which is a microcomputer with 512MB of RAM, without adding more swap space and without offloading intermediate results on disk. The recommended minimum RAM/VRAM for Stable Diffusion 1.5 is typically 8GB. Generally, major machine learning frameworks and libraries are focused on minimizing inference latency and/or maximizing throughput, all of which...
    Downloads: 21 This Week
    Last Update:
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  • 6
    TensorFlow Documentation

    TensorFlow Documentation

    TensorFlow documentation

    An end-to-end platform for machine learning. TensorFlow makes it easy to create ML models that can run in any environment. Learn how to use the intuitive APIs through interactive code samples.
    Downloads: 0 This Week
    Last Update:
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  • 7
    Face Mask Detection

    Face Mask Detection

    Face Mask Detection system based on computer vision and deep learning

    Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential...
    Downloads: 0 This Week
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  • 8
    DeepSpeech

    DeepSpeech

    Open source embedded speech-to-text engine

    DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow to make the implementation easier. A pre-trained English model is available for use and can be downloaded following the...
    Downloads: 11 This Week
    Last Update:
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  • 9
    BerryNet

    BerryNet

    Deep learning gateway on Raspberry Pi and other edge devices

    This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events...
    Downloads: 1 This Week
    Last Update:
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  • 10

    raspicam

    C++ library for controlling Raspberry Pi Camera (with/without OpenCV)

    This library allows to use the Raspberry Pi Camera. Main features: - Provides class RaspiCam for easy and full control of the camera - Provides class RaspiCam_Cv for easy control of the camera with OpenCV. - Easy compilation/installation using cmake. - No need to install development file of userland. Implementation is hidden. - Many examples
    Downloads: 2 This Week
    Last Update:
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  • 11

    Face Recognition

    World's simplest facial recognition api for Python & the command line

    Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a...
    Downloads: 2 This Week
    Last Update:
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  • 12
    TensorFlow on Raspberry Pi

    TensorFlow on Raspberry Pi

    TensorFlow for Raspberry Pi

    TensorFlow on Raspberry Pi.
    Downloads: 1 This Week
    Last Update:
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